Principal Data Engineer - Aws in Manchester

Sector: TechReference: 16038Principal Data EngineerManchester | Hybrid | Up to £85k DOEHelp shape the next chapter of our data capability. We're looking for a hands-on Principle Data Engineer to own our data platforms: dependable, well-modelled and easy to build on. This is an opportunity to own the data platforms that power analytics across the business and give a small team the tools to do its best work. What You'll Be Responsible ForAs the Principal Data Engineer, you'll own all data platforms while staying hands-on in the code. You'll work alongside Engineering and AI/Data Science, lead and develop the data team and turn business needs into a realistic plan. Own the data platforms: Build and run ingestion, orchestration, the BigQuery warehouse, DBT tooling and Python data services on GCP, including CI/CD, infrastructure as code, access and cloud costs. Keep data reliable: Set freshness and recovery targets for critical data, own alerting and incident response, and make backfills and reruns safe. Model data for the business: Design layered warehouse models, from staging to dimensional marts. Partner across teams: Work alongside Engineering and AI/Data Science to provide the data they need, and fix data issues at source. Plan the work: Turn business and analytics requests into one prioritised backlog and roadmap. Set the engineering standard: Review SQL, Python and dbt code, keep tests and contracts strong and make every production change testable and reversible. Lead and develop the team: Line-manage and mentor members of the data team, through regular 1:1s, coaching, code review and career development. Skills and ExperienceEssentialsStrong SQL and Python, building tested, maintainable production pipelines and data services. Hands-on experience with a cloud data warehouse, dbt (or equivalent) and workflow orchestration, including incremental loading, safe reruns and performance tuning. Data modelling for analytics and BI: dimensional design, semantic layers and well-documented shared datasets. Ownership of a production data platform on a major cloud: deployment, infrastructure as code, permissions, monitoring, incident recovery and cost. Sound security and data privacy practice, including GDPR and least-privilege access. Turning stakeholder needs into a prioritised backlog, and reconciling figures where finance reporting depends on them. Line management or mentoring of engineers, and technical leadership through code review and clear documentation. Experience with modern cloud data platforms, orchestration tooling, infrastructure as code and analytics platforms. DesirablesGCP experience with BigQuery, Composer and Cloud Run or Cloud Functions, including cost optimisation. Airbyte or similar ingestion tools, CDC, Kubernetes and data observability tools such as Elementary. Experience working with data scientists to put ML models or pipelines into production. What You Will GetCompetitive salaryCompetitive annual leave allowancePrivate medical insuranceFlexible working arrangements